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Real Estate Price Prediction

EasyChair Preprint no. 4926

5 pagesDate: January 22, 2021


In this paper, we have a tendency to predicting the sale value of the homes victimization numerous machine learning algorithms. Housing sales value are determined by various factors like space of the property, location of the house, material used for construction, age of the property, range of bedrooms and garages so on. This paper uses machine learning algorithms to make the prediction model for homes. Here, machine learning algorithms like supplying regression and support vector regression, Lasso Regression technique and call Tree are used to make a prognostic model. supplying Regression, SVM, Lasso Regression and call Tree show the R-squared price of 0.98, 0.96,0.81 and 0.99 severally.

Keyphrases: data cleaning, data visualization, House price forecasting, House Price Prediction, linear regression, real estate.

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Saumya Chaturvedi and Lakshya Ahlawat and Tanisha Patel and Mohammad Talha},
  title = {Real Estate Price Prediction},
  howpublished = {EasyChair Preprint no. 4926},

  year = {EasyChair, 2021}}
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